Research on Product Design and Manufacture for One-of-a-Kind Production

@PhdThesis{GangHong:thesis,
author = "Gang Hong",
title = "Research on Product Design and Manufacture for
One-of-a-Kind Production",
school = "Department of Mechanical and Manufacturing
Engineering, University of Calgary",
year = "2009",
address = "Canada",
month = "16 " # mar,
keywords = "genetic algorithms, genetic programming",
URL = "http://schulich.ucalgary.ca/mechanical/files/mechanical/Gang%20Hong-PhD%20Abstract.pdf",
abstract = "To keep competitive advantages in today's global
marketplace, many companies, especially the small and
medium enterprises, have been embracing a production
strategy, named one-of-a-kind production (OKP), which
aims at satisfying individual customer requirements
while maintaining the efficiency and quality of mass
production. This thesis work contributes to a further
understanding of one-of-a-kind production by addressing
the following three objectives to improve the
productivity in OKP companies: (1) customer information
should be incorporated in the product modelling scheme;
(2) design variations and manufacturing variations
should be well integrated, and (3) the concurrent
optimal custom product design and manufacturing should
be quickly identified based on the individual customer
requirements and manufacturing constraints.
In this thesis work, a customer-driven product modeling
scheme is introduced to incorporate customer
information into OKP product family modeling. Through
this modeling scheme, relations between customer
categories and product categories are explored to
facilitate the optimisation process to quickly identify
the custom product. In order to provide products in a
cost-effective way in addition to satisfying individual
customer needs, a hybrid modelling scheme is introduced
to model design variations and manufacturing variations
in an integrated environment. Based on the hybrid
modelling scheme, a new multi-level optimisation method
is developed to identify the optimal custom product
design and its optimal manufacturing process, where
co-evolutionary programming is used for configuration
design and numerical search is carried out for
parameter design. Two prototype systems are developed
to illustrate the effectiveness of the introduced
methodologies.",
notes = "Gang Tony Hong",
}